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Francis, Mary – ProQuest LLC, 2023
Learning analytics are starting to become standardized in higher education as institutions use the techniques of Big Data analytics to make decisions to help them reach their goals. The widespread use of student information brings forth ethical concerns primarily in relation to privacy. While the overarching ethical issues related to learning…
Descriptors: Learning Analytics, College Students, Privacy, Ethics
Wannapon Suraworachet; Qi Zhou; Mutlu Cukurova – Journal of Computer Assisted Learning, 2025
Background: Many researchers work on the design and development of multimodal collaboration support systems with AI, yet very few of these systems are mature enough to provide actionable feedback to students in real-world settings. Therefore, a notable gap exists in the literature regarding students' perceptions of such systems and the feedback…
Descriptors: Graduate Students, Student Attitudes, Artificial Intelligence, Cooperative Learning
Wollny, Sebastian; Di Mitri, Daniele; Jivet, Ioana; Muñoz-Merino, Pedro; Scheffel, Maren; Schneider, Jan; Tsai, Yi-Shan; Whitelock-Wainwright, Alexander; Gaševic, Dragan; Drachsler, Hendrik – Journal of Computer Assisted Learning, 2023
Background: Learning Analytics (LA) is an emerging field concerned with measuring, collecting, and analysing data about learners and their contexts to gain insights into learning processes. As the technology of Learning Analytics is evolving, many systems are being implemented. In this context, it is essential to understand stakeholders'…
Descriptors: Foreign Countries, College Students, Learning Analytics, Expectation
Jones, Kyle M. L.; Goben, Abigail; Perry, Michael R.; Regalado, Mariana; Salo, Dorothea; Asher, Andrew D.; Smale, Maura A.; Briney, Kristin A. – portal: Libraries and the Academy, 2023
Higher education data mining and analytics, like learning analytics, may improve learning experiences and outcomes. However, such practices are rife with student privacy concerns and other ethics issues. It is crucial that student privacy expectations and preferences are considered in the design of educational data analytics. This study forefronts…
Descriptors: College Students, Student Attitudes, Data Collection, Learning Analytics
Greenhalgh, Spencer P.; DiGiacomo, Daniela K.; Barriage, Sarah – Information and Learning Sciences, 2023
Purpose: The purpose of this paper is to examine how higher education students think about educational technologies they have previously used -- and the implications of this understanding for their awareness of datafication and privacy issues in a postsecondary context. Design/methodology/approach: The authors conducted two surveys about students'…
Descriptors: Ethics, Privacy, Learning Management Systems, Learning Analytics
O'Donoghue, Kevin – Journal of Academic Ethics, 2023
Higher education institutions are increasingly relying on learning analytics to collect voluminous amounts of data ostensibly to inform student learning interventions. The use of learning analytics, however, can result in a tension between the Council for the Advancement of Standards in Higher Education (CAS) principles of autonomy and…
Descriptors: Higher Education, Privacy, Learning Analytics, Academic Standards
Matthieu Tenzing Cisel – International Review of Research in Open and Distributed Learning, 2023
Due notably to the emergence of massive open online courses (MOOCs), stakeholders in online education have amassed extensive databases on learners throughout the past decade. Administrators of online course platforms, for instance, possess a broad spectrum of information about their users. This information spans from users' areas of interest to…
Descriptors: MOOCs, Ethics, Risk, Databases
Yueqiao Jin; Vanessa Echeverria; Lixiang Yan; Linxuan Zhao; Riordan Alfredo; Yi-Shan Tsai; Dragan Gasevic; Roberto Martinez-Maldonado – Journal of Learning Analytics, 2024
Multimodal learning analytics (MMLA) integrates novel sensing technologies and artificial intelligence algorithms, providing opportunities to enhance student reflection during complex, collaborative learning experiences. Although recent advancements in MMLA have shown its capability to generate insights into diverse learning behaviours across…
Descriptors: Learning Analytics, Accountability, Ethics, Artificial Intelligence
Barry J. Bailey – ProQuest LLC, 2021
Learning analytics systems are software designed to aggregate student data to be analyzed for the purpose of delivering information to students, with the goal of increasing student success, academic goal completion, and retention. Despite being identified as stakeholders and beneficiaries of learning analytics, student perceptions make up a small…
Descriptors: Community College Students, Student Attitudes, Learning Analytics, Ethics
Emmanuel Amos; Harry Barton Essel; George Kwame Fobiri; Akwasi Adomako Boakye; Yaw Boateng Ampadu – SAGE Open, 2025
The increasing number of students in higher education has led to the formation of large class teaching and learning environments, which is a threat to quality education. The Department of Fashion Design and Textiles Studies of Kumasi Technical University is one such department that is facing this challenge. Computer-based technology has…
Descriptors: Foreign Countries, College Students, Design, Computer Uses in Education
Whitelock-Wainwright, Alexander; Gaševic, Dragan; Tejeiro, Ricardo; Tsai, Yi-Shan; Bennett, Kate – Journal of Computer Assisted Learning, 2019
Student engagement within the development of learning analytics services in Higher Education is an important challenge to address. Despite calls for greater inclusion of stakeholders, there still remains only a small number of investigations into students' beliefs and expectations towards learning analytics services. Therefore, this paper presents…
Descriptors: Expectation, Learning Analytics, Questionnaires, College Students
Victor Manuel Corza-Vargas; Roberto Martinez-Maldonado; Boris Escalante-Ramirez; Jimena Olveres – Journal of Learning Analytics, 2024
While teachers often monitor and adjust their learning design based on students' emotional states in physical classrooms, synchronous online environments often limit their ability to perceive the emotional climate of the class. Drawing from the concept of social translucence, it is suggested that making students' emotional states…
Descriptors: Foreign Countries, Undergraduate Students, Privacy, Cultural Awareness
West, Deborah; Luzeckyj, Ann; Toohey, Danny; Vanderlelie, Jessica; Searle, Bill – Australasian Journal of Educational Technology, 2020
Increasingly learning analytics (LA) has begun utilising staff- and student-facing dashboards capturing visualisations to present data to support student success and improve learning and teaching. The use of LA is complex, multifaceted and raises many issues for consideration, including ethical and legal challenges, competing stakeholder views and…
Descriptors: College Faculty, College Administration, Ethics, Student Attitudes
West, Deborah; Luzeckyj, Ann; Searle, Bill; Toohey, Danny; Vanderlelie, Jessica; Bell, Kevin R. – Australasian Journal of Educational Technology, 2020
This article reports on a study exploring student perspectives on the collection and use of student data for learning analytics. With data collected via a mixed methods approach from 2,051 students across six Australian universities, it provides critical insights from students as a key stakeholder group. Findings indicate that while students are…
Descriptors: Stakeholders, Undergraduate Students, Graduate Students, Student Attitudes
Prestigiacomo, Rita; Hunter, Jane; Knight, Simon; Martinez Maldonado, Roberto; Lockyer, Lori – Australasian Journal of Educational Technology, 2020
Data about learning can support teachers in their decision-making processes as they design tasks aimed at improving student educational outcomes. However, to achieve systemic impact, a deeper understanding of teachers' perspectives on, and expectations for, data as evidence is required. It is critical to understand how teachers' actions align with…
Descriptors: Preservice Teachers, Preservice Teacher Education, Elementary Secondary Education, Undergraduate Students
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